7.00.02 - Forest_Predict Arguments - Aster Analytics

Teradata Aster® Analytics Foundation User GuideUpdate 2

Product
Aster Analytics
Release Number
7.00.02
Release Date
September 2017
Content Type
Programming Reference
User Guide
Publication ID
B700-1022-700K
Language
English (United States)
ModelFile
[Required if you omit both ModelTable and Forest.] Specifies the name of the text file or ZIP file that contains the trained model generated by the Forest_Drive function. You must have installed this model previously using the ACT \install command. See the note after this table.
Forest
[Required if you omit both ModelTable and ModelFile.] Specifies the name of the table that contains the decision forest generated by the Forest_Drive function. See the note after this table.
NumericInputs
[Optional] Specifies the names of the columns that contain the numeric predictor variables. Default behavior: The function gets these variables from the model generated by Forest_Drive. If you specify this argument, you must specify it exactly as you specified it in the Forest_Drive call that generated the model.
CategoricalInputs
[Optional] Specifies the names of the columns that contain the categorical predictor variables. Default behavior: The function gets these variables from the model generated by Forest_Drive. If you specify this argument, you must specify it exactly as you specified it in the Forest_Drive call that generated the model.
IDColumn
Specifies the column that contains a unique identifier for each test point in the test set.
Detailed
[Optional] Specifies whether to output detailed information about the forest trees; that is, the decision tree and the specific tree information, including task index and tree index for each tree. Default: 'false'.
Accumulate
[Optional] Specifies the names of the input columns to copy to the output table.
Either ModelTable, ModelFile, or Forest is required. If you specify ModelTable (which is recommended), the function uses it and ignores ModelFile and Forest. If you omit ModelTable and specify both ModelFile and Forest, the function uses Forest.